The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

References in zbMATH (referenced in 37 articles )

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  1. Bermanis, Amit; Salhov, Moshe; Wolf, Guy; Averbuch, Amir: Measure-based diffusion grid construction and high-dimensional data discretization (2016)
  2. Derbeko, Philip; Dolev, Shlomi; Gudes, Ehud; Sharma, Shantanu: Security and privacy aspects in Mapreduce on clouds: A survey (2016)
  3. Yang, Chao-Tung; Shih, Wen-Chung; Huang, Chih-Lin; Jiang, Fuu-Cheng; Chu, William Cheng-Chung: On construction of a distributed data storage system in cloud (2016)
  4. Zhao, Jiaqi; Tao, Jie; Streit, Achim: Enabling collaborative MapReduce on the cloud with a single-sign-on mechanism (2016)
  5. Giachetta, Roberto; Fekete, István: A case study of advancing remote sensing image analysis (2015)
  6. Green, Peter J.; Łatuszyński, Krzysztof; Pereyra, Marcelo; Robert, Christian P.: Bayesian computation: a summary of the current state, and samples backwards and forwards (2015)
  7. Hutchinson, M.; Widom, M.: Enumeration of octagonal tilings (2015)
  8. Kacfah Emani, Cheikh; Cullot, Nadine; Nicolle, Christophe: Understandable big data: a survey (2015)
  9. López, Victoria; del Río, Sara; Benítez, José Manuel; Herrera, Francisco: Cost-sensitive linguistic fuzzy rule based classification systems under the MapReduce framework for imbalanced big data (2015)
  10. Pan, C.S.; Zymbler, M.L.: Encapsulation of partitioned parallelism into open-source database management systems (2015)
  11. Sankar, M.Vishnu; Ravindran, Balaraman: Parallelization of game theoretic centrality algorithms (2015)
  12. Shahrivari, Saeed; Jalili, Saeed: Distributed discovery of frequent subgraphs of a network using MapReduce (2015)
  13. Constantine, Paul G.; Gleich, David F.; Hou, Yangyang; Templeton, Jeremy: Model reduction with MapReduce-enabled tall and skinny singular value decomposition (2014)
  14. Di, Sheng; Kondo, Derrick; Cirne, Walfredo: Google hostload prediction based on Bayesian model with optimized feature combination (2014)
  15. Kajdanowicz, Tomasz; Indyk, Wojciech; Kazienko, Przemyslaw: MapReduce approach to relational influence propagation in complex networks (2014)
  16. Kingsy Grace, R.; Manimegalai, R.: Dynamic replica placement and selection strategies in data grids -- a comprehensive survey (2014)
  17. Radenski, Atanas; Ehwerhemuepha, Louis: Speeding-up codon analysis on the cloud with local MapReduce aggregation (2014)
  18. Wei, Lifei; Zhu, Haojin; Cao, Zhenfu; Dong, Xiaolei; Jia, Weiwei; Chen, Yunlu; Vasilakos, Athanasios V.: Security and privacy for storage and computation in cloud computing (2014)
  19. Zhang, Junbo; Wong, Jian-Syuan; Li, Tianrui; Pan, Yi: A comparison of parallel large-scale knowledge acquisition using rough set theory on different MapReduce runtime systems (2014)
  20. Zhang, Xuyun; Liu, Chang; Nepal, Surya; Yang, Chi; Dou, Wanchun; Chen, Jinjun: A hybrid approach for scalable sub-tree anonymization over big data using MapReduce on cloud (2014)

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